Kristen Greene

2022

A researcher in the Science corpus: 1 paper; trusts 0 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Papers from Kristen Greene's perspective

Ordered by how strongly the researchers Kristen Greene trusts endorse each paper. Same corpus, a different order for every researcher.

1. Language Models are Few-Shot Learners (Neural Information Processing Systems)
2. Big Data's Disparate Impact
3. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification
4. Datasheets for datasets
5. Semantics derived automatically from language corpora contain human-like biases
6. Model Cards for Model Reporting
7. Counterfactual Fairness (Neural Information Processing Systems)
8. Language (Technology) is Power: A Critical Survey of “Bias” in NLP
9. Avoiding Discrimination through Causal Reasoning
10. A Framework for Understanding Unintended Consequences of Machine Learning

Their papers

• Towards a Standard for Identifying and Managing Bias in Artificial Intelligence (2022)